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Motivated by a Bayesian vision of the 3D multi-view reconstruction from images problem, we propose a dense 3D reconstruction technique that jointly refines the shape and the camera parameters of a scene by minimizing the photometric reprojection error between a generated model and the observed images, hence considering all pixels in the original images. The minimization is performed using a gradient...
In this paper, we propose a method to detect changes in the geometry of a city using panoramic images captured by a car driving around the city. We designed our approach to account for all the challenges involved in a large scale application of change detection, such as, inaccuracies in the input geometry, errors in the geo-location data of the images, as well as, the limited amount of information...
This paper presents a framework for classification and pose estimation of vehicles in videos by assuming their given 3D models. We rank possible poses and types for each frame and exploit temporal coherence between consecutive frames for refinement. As a novelty, first, we cast the estimation of a vehicle's pose and type as a solution of a continuous optimization problem over space and time. Due to...
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